Marketers Hesitate Adopting AI for Influencer and CTV
Digiday+ Research reports that a Q1 2026 survey of more than 100 marketing professionals found marketers using AI more readily in social and retail media than in influencer or CTV marketing. The article's most concrete figure is that only 25% of marketers said they use AI for influencer marketing. For AI product and data teams, the result points to a practical adoption gap: channels with cleaner signals and APIs are easier to automate, while influencer and connected-TV workflows still depend on subjective creative judgment, partner fragmentation, brand-safety review and harder attribution. That makes measurement infrastructure at least as important as model capability.
The useful lesson for AI builders is that marketing automation adoption follows measurement quality. Channels with richer first-party signals and standardized APIs tend to absorb AI faster, while influencer and CTV workflows expose the messy edge cases around brand safety, attribution and subjective creative judgment.
What happened
Digiday+ Research reports that a Q1 2026 survey of more than 100 marketing professionals found advertisers using AI more readily for social media and retail media marketing than for influencer or connected-TV marketing. The reported figure most relevant to product planning is that 25% of marketers said they use AI for influencer marketing.
Industry context
Influencer marketing mixes qualitative brand fit, creator contracts, audience trust and creative review. CTV adds fragmented measurement, household identity constraints and cross-device attribution challenges. Those are not problems a generic model solves by itself; they require workflow design, trustworthy data joins and human review.
For practitioners
Teams building marketing AI should prioritize instrumentation before promising automation. Useful features include human-in-the-loop approval, explainable recommendations, privacy-aware identity resolution, incrementality testing and integrations that preserve campaign context across partners.
What to watch
Watch whether vendors can turn influencer and CTV data into repeatable benchmarks. If measurement remains inconsistent, adoption will likely concentrate in assistant workflows and planning tools rather than full campaign automation.
Key Points
- 1The Digiday+ survey suggests AI adoption is strongest where campaign signals and APIs are easiest to standardize.
- 2Influencer and CTV workflows remain harder because attribution, brand safety and partner data are fragmented.
- 3Marketing AI vendors should prioritize measurement, review workflows and explainability before promising full automation.
Scoring Rationale
This is a solid industry-adoption signal for marketing AI, especially because it identifies channel-specific friction. The impact is limited by reliance on one trade survey and by the absence of direct platform or regulatory change.
Sources
Public references used for this report.
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